Arthroscopic Treatment of Cam‐Type Impingement for Femoroacetabular Impingement Using Patient's Own 1:1 Three‐Dimensional Printed Hip Model Without the Use of Fluoroscopy
Bibliographic record
Abstract
The arthroscopic treatment of femoroacetabular impingement (FAI) has increased greatly in popularity over the past decades. Treatment involves the resection of abnormal bony morphology of the femoral head/neck (cam-type) and the acetabulum (pincer-type), which otherwise create damage from the pathologic contact between the 2 structures. More recently, in evaluating the postoperative success of FAI surgery, unsuccessful resection of the cam impingement has been identified as a leading cause for revision. To evaluate adequate cam resection intraoperatively, C-arm fluoroscopy is most commonly used. However, fluoroscopy has disadvantages, including its limited availability in smaller surgical centers, radiation exposure, and it only provides 2-dimensional information of a 3-dimensional problem. With the recent implementation of ultrasound-guided portal placement, a technique for adequate cam resection is the last barrier to eliminating the need for intraoperative imaging for FAI. We present a technique that uses a 1:1 3-dimensional printed model made from computed tomography scans that have the patient's unique anatomy, to better identify and quantify the resection of cam-type impingements. This technique is reproducible and can lead to better understanding of the cam resection for each individual patient. Further, when combined with ultrasound-guided portal placement, it eliminates the need for intraoperative fluoroscopy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".